How AINNA NeuralOps is Wired: 私密 vLLM 服务器, VPN 分段, VPS 智能体层, 分离式系统 and Hermes
从 the engineering side, we built NeuralOps as a segmented, modular AI stack. The LLM server is deliberately not reachable from the public internet.
The inference backbone is a private LLM server running vLLM, loaded with up to 7 LLM models to cover different operational workloads. It sits entirely inside a VPN 加密保护 private network, and admin access is gated to authorized users only through that VPN tunnel.
Public internet has zero direct path into the LLM server.
No public admin panel.
No exposed model backend.
No open inference ports.
No direct GPU access.
No extra attack surface we do not need.
The VPS layer is not there to serve models to the internet.
It acts as the agent execution layer. That is where we run OpenClaw or OpenCode agents, alongside 分离式系统 and Hermes operational 工作流.
Each VPS is isolated at the cloud level from every other VPS. That separation keeps workloads from bleeding into each other and lets each agent, service or operational process 实时 inside its own bounded environment.
快照s are part of the recovery playbook. Before a big deployment or an agent-driven 系统 change, we snapshot the VPS. If something breaks, we roll back to the last known-good state fast. That makes experimentation, automation and agent execution safer without putting the wider infrastructure at risk.
The VPS layer runs controlled execution tasks such as:
OpenClaw / OpenCode agent execution
系统 auditing
website monitoring
automation 工作流
独立系统 operations
Hermes integration
logs and reporting 工作流
lightweight orchestration between services
snapshot-based recovery and rollback
The LLM server stays behind the VPN. The VPS talks to it over a controlled private route, hitting a restricted inference API with a narrow access policy. The agents can request model output, but they never get broad access to the LLM server environment.
That separation gives every layer a clear job.
The LLM server is the inference layer.
The VPS is the agent execution layer.
The 独立系统 is the operational workflow layer.
The Hermes 系统 is the internal business operations layer.
The VPN is the security boundary.
The cloud snapshot is the recovery layer.
By keeping those responsibilities apart, NeuralOps gets more secure, more scalable and easier to run. One bad VPS does not poison the others. A broken agent workflow gets rolled back from snapshot. A VPS-layer incident never touches the LLM server behind VPN. 时间 Hermes needs automation, reporting or operational processing, it routes through the 独立系统 instead of calling the LLM backend directly.
AINNA NeuralOps is not a chatbot bolted onto a server.
It is a modular AI operations stack built for real business 工作流:
私有 LLM 服务器 + vLLM + VPN + Isolated VPS 智能体层 + 云 快照s + 独立系统 + Hermes
This stack gives us tighter control over AI execution, model access, operational automation, 系统 recovery, security boundaries and long-term scalability.
良好 AI infrastructure is not only about benchmark scores.
It is about control.
It is about isolation.
It is about auditability.
It is about maintainability.
It is about recoverability.
And most importantly, it is about keeping the crown jewels off the public internet.
https://masli.bond/ainna-ai/ - Our LLM 服务器
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总结部分让automation and agent execution safer的重点更加清楚。
同意作者对service or operational process 实时的判断，方向很清楚。
关于良好 AI infrastructure的说明很完整，基础部分尤其清楚。
文章对security boundaries and long-term scalability的结论比较平衡，不只是强调好处。
先存起来，主要是为了7。
我喜欢7这部分，因为它讲得比较务实。
这篇文章适合团队用来开始讨论AINNA neuralops。
文章把从 the engineering side和日常运营联系起来，这一点很有帮助。